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---
base_model: AIRI-Institute/gena-lm-bert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results_short_multi
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# results_short_multi
This model is a fine-tuned version of [AIRI-Institute/gena-lm-bert-base](https://huggingface.co/AIRI-Institute/gena-lm-bert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6943
- Accuracy: 0.4984
- F1: 0.6652
- Precision: 0.4984
- Recall: 1.0
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6893 | 1.0 | 3125 | 0.6936 | 0.5025 | 0.6689 | 0.5025 | 1.0 |
| 0.7022 | 2.0 | 6250 | 0.6948 | 0.5025 | 0.6689 | 0.5025 | 1.0 |
| 0.6899 | 3.0 | 9375 | 0.6940 | 0.5025 | 0.6689 | 0.5025 | 1.0 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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